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<table width="100%"><tr><td>goodclassif(modtools)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
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<h2>Good classification</h2>


<h3>Description</h3>

<p>
This function gives the percentage of good classification in confusion matrix.
</p>


<h3>Usage</h3>

<pre>
goodclassif(x)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>x</code></td>
<td>
a matrix or data.frame</td></tr>
</table>

<h3>Value</h3>

<p>
~Describe the value returned
If it is a LIST, use
</p>
<table summary="R argblock">
<tr valign="top"><td><code>comp1 </code></td>
<td>
Description of 'comp1'</td></tr>
<tr valign="top"><td><code>comp2 </code></td>
<td>
Description of 'comp2'</td></tr>
</table>
<p>

...</p>

<h3>Note</h3>

<p>
~~further notes~~
+ description des matrices de confusion
</p>
<p>
sum de la diagonale
</p>


<h3>References</h3>

<p>
~put references to the literature/web site here ~
</p>


<h3>See Also</h3>

<p>
<code><a onclick="findlink('base', 'kappa.html')" style="text-decoration: underline; color: blue; cursor: hand">kappa</a></code>,<code><a href="roc.html">roc</a></code>
</p>


<h3>Examples</h3>

<pre>
##---- Should be DIRECTLY executable !! ----
##-- ==&gt;  Define data, use random,
##--    or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x) 
{
    if (ncol(x) != nrow(x)) 
        stop("non covenient dimension !")
    N &lt;- sum(x)
    sxii &lt;- sum(diag(x))
    return(sxii/N)
  }
</pre>

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